Fully Automated Point Spread Function Analysis Using Pycalibrate

Abstract

AbstractReproducibility is severely limited if instrument performance is assumed rather than measured. Within optical microscopy, instrument performance is typically measured using sub-resolution fluorescent beads. However, the process is performed infrequently as it is requires time and suitably trained staff to acquire and then process the bead images. Analysis software still requires the manual entry of imaging parameters. Human error from repeatedly typing these parameters can significantly affect the outcome of the analysis, rendering the results less reproducibile. To avoid this issue, PyCalibrate has been developed to fully automate the analysis of bead images. PyCalibrate can be accessed either by executing the Python code locally or via a user-friendly web portal to further improve accessibility when moving between locations and machines. PyCalibrate interfaces with the BioFormats library to make it compatible with a wide range of proprietary image formats. In this study, PyCalibrate analysis performance is directly compared with alternative free-access analysis software PSFj, MetroloJ QC and DayBook3 and is demonstrated to have equivalent performance but without the need for user supervision.